Cartoon Dubbing for Improving Students’ Speaking Ability in Transactional Conversation (a classroom action research into the eighth graders of SMP 5 Semarang in the academic year of 2011/ 2012)
Bibliographic record
Abstract
The aim of this study was to know the effectiveness of using cartoon dubbing in teaching speaking of transactional conversations. Objectives of the study were: to know the implementation of cartoon dubbing used for improving students’ ability in transactional conversation, to find out the use of cartoon dubbing for improving students’ speaking ability in transactional conversation and, to find out advantages and disadvantages the cartoon dubbing for improving students’ speaking ability in transactional conversations. A classroom action research was conducted in this research. The subject of this study was the eighth graders of SMP 5 Semarang. The students were in class 8D and there were 22 students in the class. In this research there were five meetings were conducted. The first meeting was pretest. The second and third meetings conducted for cycle 1. The fourth meeting was used for cycle 2 and the last meeting was posttest and questionnaire. Based on the analysis of the students’ dubbing and performances that were recorded, it can be concluded that the students’ speaking ability improved. This improvement can be seen from the mean scores of each element of speaking, informal interview, observation notes, and questionnaires that was analyzed. The observation notes were made to analyze and see the students’ activity during the teaching process. According to the questionnaires and informal interview that I used, the students interested to the medium. Based on the result of the study, their average in pre-test was 68.9, then it became 73.4 in formative-test, and finally their average score obtained 79.2 on post-test. It indicates that the cartoon dubbing is an effective medium in helping students to improve their skill in speaking of transactional conversations. The advantages of cartoon dubbing were: reducing mispronunciation, improving the fluency, raising the awareness of intonation, linking the pronunciation with actual use and built learners’ perceptions. The disadvantages were: consuming time to prepare and demanding teacher to be skillful in making the cartoon dubbing. The suggestion is given to the teacher is that the teacher should use the cartoon dubbing for improving students speaking ability; it can be seen from the improvement of students’ score on the result above. It also helps for making the lesson interesting and fun.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.118 | 0.018 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".